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Thomas Stanley, Dalia B. Kirschbaum, George J. Huffman, and Robert F. Adler

TMPA-RT and IMERG-L rainfall estimates. In quantile mapping, a value from one product is used to look up the value of the second product at the same quantile. For example, if a TMPA-RT precipitation threshold was 180 mm day −1 , the equivalent IMERG-L value would be 231 mm day −1 . Fourth, the quantile-mapped version of LHASA was run with IMERG-L data. The performance of the adapted rainfall thresholds was evaluated by a comparison to the original TMPA-based model. The true positive rate (TPR) was

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Jiaying Zhang, Liao-Fan Lin, and Rafael L. Bras

variations begs the question of whether temperature could be an indicator of quality. Complementing satellite precipitation products are those from numerical weather prediction (NWP) models that show good performance at high latitudes and during cold seasons and poor performance at the tropics and during warm seasons ( Adler et al. 2001 ; Gottschalck et al. 2005 ; Ebert et al. 2007 ; Kidd et al. 2012 ). For example, McBride and Ebert (2000) evaluated NWP model precipitation over Australia by

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Randy J. Chase, Stephen W. Nesbitt, and Greg M. McFarquhar

for the evaluation of atmospheric numerical model simulations and their parameterized ice-phase microphysics (e.g., Delanoë et al. 2011 ; Stein et al. 2015 ; Ori et al. 2020 ). Despite many advances in satellite remote sensing techniques and sensors in the past few decades, the uncertainty in the estimate of the atmosphere’s ice water path remains large, and there is poor agreement between observational retrievals and numerical models (e.g., Duncan and Eriksson 2018 ). The best way to retrieve

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Sybille Y. Schoger, Dmitri Moisseev, Annakaisa von Lerber, Susanne Crewell, and Kerstin Ebell

-A). The performance of the newly developed relationships is then evaluated for three case studies. A summary of the results and conclusions can be found in section 5 . 2. Measurement setup a. Measurement site Hyytiälä The University of Helsinki operates a Forestry Field Station in southern Finland, in Hyytiälä (61.8439°N, 24.2875°E; 150 m above mean sea level), 220 km northwest of Helsinki ( Hari and Kulmala 2005 ). Meteorological instrumentation, including the PIP, is operated in the middle of a

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Jackson Tan, Walter A. Petersen, Pierre-Emmanuel Kirstetter, and Yudong Tian

– 9 evaluate the performance of IMERG and TMPA in identifying rain rates of raining events. They showed that both satellite estimates generally have improved performance at larger spatial scale and longer temporal scale, both for systematic and random errors. The decomposition using the more relevant multiplicative error model, however, suggests that the improvement is more subtle: upscaling improves the range of rain rates in the estimates as compared to the reference, but it also adds an

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Liang Liao and Robert Meneghini

the use of the DFR. On the other hand, this approach loses the capability of fully accounting for the DSD variations along the profile because a single adjustment factor is not able to account for variations in the DSD along the profile. In fact, the performance depends on a number of factors that include the model assumptions and the degree of uniformity of the DSD along the profiles. An evaluation of the algorithm performance is important in assessing the strengths and weaknesses of the

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Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, and F. Joseph Turk

; Zhang et al. 2011 , 2016 ). The outputs of a high-fidelity mesoscale simulation model are also used for further evaluation of the results over high altitudes, during the Olympic Mountains Experiment (OLYMPEX) in 2015 ( Houze et al. 2017 ). The paper is structured as follows. Section 2 briefly describes the database and the phase detection method used on the operational GPM radar and radiometer products. Section 3 elaborates on the effects of snow cover on passive microwave signal of snowfall at

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Md. Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, and Emmanouil N. Anagnostou

performance because they treat each data point as an independent holdout sample. However, complex topography and regional climate characteristics play a vital role in controlling the spatial pattern of precipitation ( Block and Rajagopalan 2007 ; Enyew and Steeneveld 2014 ). Moreover, accurate estimate of precipitation can be a challenging task when the quality of the validation dataset is low or the site is ungauged. The leave-one-region-out experiment is evaluating the model under this condition by

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Jackson Tan, Walter A. Petersen, and Ali Tokay

grid box are 100, chiefly due to the flatness of the region and the proximity of the radar at Dover Air Force Base, Delaware (~80 km). Nevertheless, we mask MRMS pixels with RQI less than 100, thus keeping only perfect-RQI MRMS pixels in computing the areal averages. For most parts in this study, MRMS is used not as a ground reference but as a context against which the performance of IMERG is compared. d. Approach In our study, we adopt the proposal suggested by Tang et al. (2015) and evaluate

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Yonghe Liu, Jinming Feng, Zongliang Yang, Yonghong Hu, and Jianlin Li

locations for this station. Step 4 is to use the selected predictor values to train each single-station downscaling model (GLM or ANN). In step 5, the performance of each single-station downscaling model is tested and then the Pearson’s correlation coefficients (Pearson R ) between the downscaled and observed logarithmic precipitation are calculated for both the calibration period and the validation period. The sixth step is to define a 0.1° × 0.1° dense grid that covers the study region. The distances

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